PHM Fundamentals and Case Studies Online Short Course
Course Dates: October 14, 15, 16, 19, & 20, 2020 from 1:00 – 5:15 EDT (UTC-4:00)
Course Leaders: Dr. Karl Reichard and Jeff Bird
Course Presenters: Specialists using proven PHM Society curriculum, case studies and mini-workshops
Course Administrator: Jeff Bird jeffbird@rogers.com
Overview
The PHM Society offers this updated intensive short course titled PHM Fundamentals and Case Studies— From Monitoring/Sensing to Fault Diagnosis/Failure Prognosis and Case Studies, on PHM tools, methods, applications and case studies as an on-line course spread over18 hours over five days. This follows from the first offering at the PHM14 conference in Fort Worth, TX with 48 attendees and regular ratings of 4/5. It was also run in 2015 in San Diego, 2016 in both Bilbao, Spain and Denver USA, in St. Petersburg, USA in 2017, Philadelphia in 2018, Utrecht, Netherlands in July 2018 and Scottsdale at PHM19.
As in the previous offerings, the course will be taught by recognized international experts in the PHM field and will cover the current state of the art in PHM technologies, sensors and sensing strategies, data mining tools, CBM+ technologies, novel diagnostic and prognostic algorithms as well as a diverse array of application examples/case studies. It is addressed to engineers, scientists, operations managers, educators, small business principals and system designers interested to learn how these emerging technologies can impact their work environment.
Through a lecture (with Q&A), networking and workshop format with specialist experts, participants will:
- Establish a baseline for defining the extent and capabilities of PHM, specifically needs and organization
- Identify specific details of PHM Applications (metrics, sensors, cost benefits, reliability) and PHM Methods (diagnostics, prognostics, data driven methods and uncertainty)
- Identify issues and needs and a way forward including Continuing Professional Development
- Examine case studies of PHM applications across diverse domains to identify solutions and impacts
- Plan a PHM application in two mini workshop settings with expert group leaders
Course Credit
A PHM Society Certificate can be provided for 1.8 Continuing Professional Development Units to each participant completing the course, on request.
Course Details
- Background reading and references:
http://www.phmsociety.org/references/documents/recommended-reading - Course notes will be available to be printed and shipped to students. (Details to follow for the registered participants.)
- Workshop topic: We will work in small groups on small realistic problems. Participants are asked to submit a problem statement from their organization: Problem definition, asset of interest, health management objectives, and customer(s).
- Segment 1: developing PHM requirements—needs, stakeholders and metrics
- Segment 2: data and modeling approaches, operational issues.
Course Outline
| Day 1 – Wed, 10/14/20 (ET) | Foundations and Methods | Speaker |
|---|---|---|
| 1:00 to 1:20 | Welcome and Introductions (All participants) | Jeff Bird, TECnos |
| 1:20 to 2:00 | 1 Introduction to PHM (Taxonomy, scope, basics, standards – for all talks) | Jeff |
| 2:00 to 2:45 | 2 Deriving Requirements for PHM | Abhinav Saxena, GE |
| 2:45 to 3:30 | 3 Case Study for Requirements/metrics | Abhinav |
| 3:30 to 3:45 | Break | |
| 3:45 to 4:30 | 4 Diagnostics Methods | José Celaya, Schlumberger |
| 4:30 to 5:00 | 5 Case Study for Diagnostics | José |
| 5:00 to 5:15 | Wrap-up and Compilation of Issues | All |
| Day 2 – Thu, 10/15/20 (ET) | Methods and Project Plan Workshop | Speaker |
| 1:00 to 1:45 | 6 Failure Prognostics | Abhinav |
| 1:45 to 2:10 | 7 Case Study for Prognostics | Abhinav |
| 2:10 to 2:55 | 8 Data Analytics Methods | Neil Eklund, PARC |
| 2:55 to 3:20 | 9 Case Study for Data Analytics | Neil |
| 3:20 to 3:30 | Break | |
| 3:30 to 4:15 | 10 Sensors and Sensor Strategies | Karl Reichard, Penn State |
| 4:15 to 5:00 | 11 PHM Project Workshop – Problem, Stakeholders, Metrics (Small group data design activity with worksheets) | All then Breakouts |
| 5:00 to 5:15 | 11 Summary of workshop results (Each group prepares their own results for presentation on Day 3 pm ) | Breakouts |
| Day 3 – Fri, 10/16/20 (ET) | PHM Business and Plenary | Speaker |
| 1:00 to 1:30 | 11 Summary of workshop results (Each group reports results) | Jeff and Karl |
| 1:30 to 2:10 | 12 CBM+ and IVHM Technologies | Karl |
| 2:10 to 2:50 | 13 PHM Performance Metrics | Abhinav |
| 2:50 to 2:55 | Short break | |
| 2:55 to 3:30 | 14 PHM Cost Benefit Analysis | Jeff |
| 3:30 to 4:15 | 15 Reliability and Life Cycle Management | José |
| 4:15 to 4:45 | 16 Fielded Systems Case Study for Reliability | José |
| 4:45 to 4:50 | Short break | |
| 4:50 to 5:00 | 17 PHM Planning Workshop Introduction – Models and Operational Issues (Small group activity builds on workshop 1) | Jeff |
| 5:00 to 5:15 | Wrap-up and Compilation of Issues | All |
| Day 4 – Mon 10/19/20 (ET) | Case Studies and PHM Project Workshop | Speaker |
| 1:00 to 1:45 | 18 Fielded Systems Case Study for CBM | Karl |
| 1:45 to 2:30 | 19 Fielded Systems Case Study for Cost Benefit Analysis Bearings | Neil |
| 2:30 to 2:45 | 17 PHM Project Planning Workshop – Models and Operational Issues (Introduction and set up of small group activity) | All then Breakouts |
| 2:45 to 3:15 | 17 PHM Project Planning Workshop (Small group activity) | Breakouts |
| 3:15 to 3:30 | Break | |
| 3:30 to 4:15 | 17 PHM Project Planning Workshop (Small group activity) | Breakouts |
| 4:15 to 4:45 | 17 PHM Project Planning Workshop (Small groups prepare their own report for presentation on Day 5 pm) | Breakouts |
| 4:45 to 5:00 | Wrap-up | Breakouts |
| Day 5 – Tue, 10/20/20 (ET) | Case Studies and PHM Project Workshop | Speaker |
| 1:00 to 1:10 | Introduction | Jeff |
| 1:10 to 2:10 | 17 PHM Project Planning Workshops review and discussion (Small groups reporting) | All |
| 2:10 to 3:15 | 20 Plenary – Issues and Needs and Priorities (Review to compile collected issues from all participants, then prioritize) | All |
| 3:15 to 3:30 | Break | |
| 3:30 to 4:00 | 21 Way forward (Paths, Resources, Continuing Professional Development) | Jeff and Karl |
| 4:00 to 4:15 | Wrap-up 22 Evaluation Forms |
All |
Course Presenters
Experienced PHMers will present the tuned PHM Society content and also lead the mini-workshop small group discussions. Interactions are encouraged.
Jeff Bird is currently a consultant with TECnos Consulting Services, Ottawa, Canada. His present avocations include advancing the art, science and business of prognostics and health management in diverse fields. Specifically, he leads PHM Society board initiatives in Education and Professional Development as well as Standards. He recently completed one career spanning 30 years as a Research Officer at the Gas Turbine Laboratory of the National Research Council Canada. His published research there was on gas turbine dynamics and performance, health monitoring and management, adverse environments, and uncertainty. Previously he worked as an Operational Research scientific officer in the Department of National Defence where he enjoyed contributing to airlift and search and rescue planning. He studied at the University of Toronto (Engineering Science- Aerospace) and at Carleton University (Mechanical, Aerospace and Systems).
Dr. José R. Celaya is a Principal Scientist and Machine Learning Technical Lead Manager with the Software Technology Innovation Center, Schlumberger in Menlo Park, CA. He was previously a Research Scientist (contractor) in the Prognostics Center of Excellence and the Diagnostics and Prognostics Group Co-Lead at NASA Ames Research Center. He received a Ph.D. degree in Decision Sciences and Engineering Systems in 2008, a M. E. degree in Operations Research and Statistics in 2008, a M. S. degree in Electrical Engineering in 2003, all from Rensselaer Polytechnic Institute; and a B. S. in Cybernetics Engineering in 2001 from CETYS University, Mexico.
https://www.linkedin.com/in/josecelaya/
https://scholar.google.com/citations?user=RC3TO0EAAAAJ&hl=en
Dr. Neil Eklund is an experienced technologist in the space of data science, Industrial Artificial Intelligence, machine learning, and evolutionary algorithms for multi-objective optimization, with significant experience in developing fielded solutions to industrial problems. With 20 years of deep technical experience across multiple industry segments – Aerospace, Energy, Healthcare, Finance, Rail, Oil & Gas, and US Government Research (DARPA; NASA, Department of Defense) – he has been the technical lead on a wide range of high-impact projects, resulting in 16 patents, with another four pending, and over 70 technical publications. Dr. Eklund has worked at some of the largest companies in the world – including General Electric Research and Schlumberger – and also a couple of five-person start-ups. This has allowed him to work on a wide variety of research projects, from early detection of cataract using intraocular photoluminescence to multi-objective bond portfolio optimization. Most recently, his work has focused on fielded, commercially viable asset management systems related to remote monitoring and diagnostics for military and commercial aircraft and oil & gas equipment. He currently works at the Palo Alto Research Centre in data analytics.
Dr. Karl Reichard has over 25 years of experience in the design and development of advanced measurement, control and monitoring systems. He received the Ph.D., M.S. and B.S. degrees in Electrical Engineering from the Virginia Polytechnic Institute and State University (Virginia Tech). Dr. Reichard is a Dr. Reichard is an Associate Research Professor with the Pennsylvania State University Applied Research Laboratory and the Penn State Graduate Program in Acoustics. His research experience includes the development of embedded and distributed sensing and control systems for machinery and system health monitoring, acoustic surveillance and detection, active noise and vibration control and electro-optics. Dr. Reichard is a member of the Board of Directors of the Prognostics and Health Management Society, and a member of the IEEE and the Acoustical Society of America. He is the author of over 50 papers and articles published in journals and conference proceedings.
Dr. Abhinav Saxena is a Senior Scientist in AI & Learning Systems organization at GE Global Research Center. Abhinav is currently involved with developing PHM solutions for various industrial systems at GE and driving integration of PHM analytics in GE’s industrial internet platform. Abhinav is also an adjunct professor in the Division of Operation and Maintenance Engineering at Luleå University of Technology, Sweden. Prior to GE, Abhinav was a Research Scientist with SGT Inc. at NASA Ames Research Center for over seven years. Abhinav’s interests lie in developing PHM methods and algorithms with special emphasis on data-driven methods for practical prognostics. He has done extensive work on PHM performance evaluation, PHM requirements, and verification and validation of prognostics. He actively participates in several SAE standards committees, IEEE prognostics standards committee, and various PHM Society educational activities, and is a Fellow of the PHM Society. He is also the chief editor of International Journal of Prognostics and Health Management since 2011 and actively participates in organization of PHM Society conferences.
For information contact shortcourse@phmconference.org